Today at the Consumer Electronics Show, Nvidia CEO Jensen Huang officially launched the company’s new Rubin computing architecture, which he described as the latest in AI hardware. The new architecture is currently in production and is expected to increase further in the second half of the year.
“Vera Rubin is designed to solve this fundamental challenge that we have: The amount of computation needed for AI is skyrocketing.” Huang told the crowd. “Today I can tell you that Vera Rubin is in full production.”
The Rubin architecture, first announced in 2024, is the latest result of Nvidia’s relentless hardware development cycle that has turned Nvidia into the most valuable company in the world. The Rubin architecture will replace the Blackwell architecture, which in turn replaced the Hopper and Lovelace architectures.
Rubin chips are already planned for use by nearly every major cloud provider, including high-profile Nvidia partnerships with Anthropic, OpenAI and Amazon Web Services. Rubin systems will also be used in HPE’s Blue Lion supercomputer and the upcoming Doudna supercomputer at Lawrence Berkeley National Lab.
Named after astronomer Vera Florence Cooper Rubin, the Rubin architecture consists of six separate chips designed to be used together. The Rubin GPU takes center stage, but the architecture also addresses growing storage and interconnect bottlenecks with new improvements in the Bluefield and NVLink systems, respectively. The architecture also includes a new Vera CPU, designed for agentic reasoning.
Explaining the benefits of the new storage, Nvidia’s senior director of AI infrastructure solutions, Dion Harris, pointed to the growing cache-related memory requirements of modern AI systems.
“When you start enabling new types of workflows, like agent AI or long-term tasks, that puts a lot of stress and demands on your KV cache,” Harris told reporters on a call, referring to a memory system used by AI models to condense input. “So we’ve introduced a new storage pool that connects externally to the compute device, which allows you to scale your storage pool much more efficiently.”
Techcrunch event
San Francisco
|
13.-15. October 2026
As expected, the new architecture also represents a significant advance in speed and power efficiency. According to Nvidia’s tests, the Rubin architecture will perform three and a half times faster than the previous Blackwell architecture on model training tasks and five times faster on inference tasks, reaching as high as 50 petaflops. The new platform will also support eight times more inference computation per watts.
Rubin’s new capabilities come amid intense competition to build AI infrastructure, which has seen both AI labs and cloud providers scramble for Nvidia chips as well as the facilities needed to power them. On an earnings call in October 2025, Huang estimated that between $3 trillion and $4 trillion will be spent on AI infrastructure over the next five years.